Computable analysis by Oliver Aberth

By Oliver Aberth

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PostgreSQL. org/ 11. TPC-H Decision Support Benchmark. cn 2 University of the Chinese Academy of Sciences, Beijing, China Abstract. In the original MapReduce model, reduce tasks need to fetch output data of map tasks in the manner of “pull”. However, reduce tasks which are occupying reduce slots cannot start executing until all the corresponding map tasks are completed. It forms the dependence between map and reduce tasks, which is called the coupled relationship in this paper. The coupled relationship leads to two problems: reduce slot hoarding and underutilized network bandwidth.

However as the number of concurrent queries Data Warehouse Processing Scale-Up for Massive Concurrent Queries with SPIN 19 increase we observe a significant drop in throughput as the running queries exhaust the available memory. SPIN, does not have these memory issues and can be massively partitioned among low-end commodity servers. 000 50 0 Througput (Qph) - SF10 0 1 2 10 20 75 100 #Concurrent queries 1 2 10 20 75 100 #Concurrent queries Fig. 16. Throughput for varying query loads with (a) SF = 1 and (b) SF = 10 (higher is better) This effect can be observed in Fig.

Job scheduling for multi-user MapReduce clusters. Technical report UCB/EECS2009-55, EECS Department, University of California, Berkeley (2009) 27. : Spark: cluster computing with working sets. edu Abstract. This paper addresses causal inference and modeling over event streams where data have high throughput, are unbounded, and may arrive out of order. The availability of large amount of data with these characteristics presents several new challenges related to causal modeling, such as the need for fast causal inference operations while ensuring consistent and valid results.

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